JpGU-AGU Joint Meeting 2017

Presentation information

[EE] Poster

H (Human Geosciences) » H-GM Geomorphology

[H-GM03] [EE] Geomorphology

Mon. May 22, 2017 3:30 PM - 5:00 PM Poster Hall (International Exhibition Hall HALL7)

convener:Hiroshi Shimazu(Department of Geography, Faculty of Geo-Environmental Science, Rissho University), Masayuki Seto(Fukushima Future Center for Regional Revitalization, Fukushima University)

[HGM03-P01] Stochasticity controls and the central role of “internal variability” in soil erosion system

*Jongho Kim1, Valeriy Ivanov2, Simone Fatichi3 (1.Sejong University, 2.University of Michigan, 3.ETH Zurich)

Keywords:Soil erosion, Geomorphic Internal Variability, Geomorphic External Variability, Stochasticity index, Soil erosion variability

Accurate prediction of soil loss rates remains a problem because erosion exhibits a non-unique behavior given the same rainfall/runoff forcing. The effects and causes of uncertainties in soil surface erodibility resulting in such a behavior have not been fully addressed from a mechanistic perspective in previous research. We use a large database of empirical data on soil loss and a comprehensive physical model of runoff – overland flow – erosion – transport processes that dynamically updates the mass and composition of soil substrate at the hydrologic-event scale to address reasons of unpredictability in soil erosion. We explain the role of micro-scale erodibility (referred to here as ‘geomorphic internal variability’) on geomorphic response, which acts as an intermediary between larger-scale forcings and soil loss response. Accounting for a possible range of internal variability illustrates the high sensitivity of erosion response to initial conditions of soil bed, resulting in extremely large uncertainties in short-term predictions. Furthermore, the reduction of geomorphic response variability at larger temporal scales is primarily attributed to a ‘compensation effect’: temporal alternation of events that exhibit either ‘source-limited’ or ‘transport-limited’ regimes. We relate this reduction to a novel stochasticity index that reflects the degree of variability of intra- and inter-event hydrometeorologic conditions. A higher stochasticity index implies a larger reduction of soil loss variability (higher predictability) at the aggregated temporal scales with respect to the mean hydrologic forcing.

Acknowledgement:
This study was supported by the Basic Science Research Program of the National Research Foundation of Korea funded by the Ministry of Education (2016R1D1A1B03931886).